Lipidomics: What does the future hold?

The area of lipidomics is relatively new: although publications on MS-based analysis of cellular lipids started to emerge in the early 1990s, the actual term lipidomics appeared in the literature in 2003. However, in the short space of less than 10 years, lipidomics has emerged as an extremely valuable tool for biosciences 1-4. Large research networks (e.g. LIPID MAPS in USA, LipidomicsNet in Europe, etc.), smaller consortia and specialised laboratories around the world have focused their effort towards standardising experimental protocols and lipid nomenclature, whilst attempting to map the lipidome of model systems, cells, tissues and body fluids, and in this way gain new information into the role of lipid networks in health and disease. At the same time there is an increased awareness of the field with more conferences organising sessions on lipids and lipidomics, and societies such as EuroFedLipid, forming interest groups and divisions. We cannot dispute the fact that lipidomics owes its existence to modern MS. Although other technologies are relevant and continue to offer valuable service to lipid analysis and biology, MS is the primary methodology that allows qualitative and quantitative assessment of multiple lipid species, and can generate the large data sets needed for mapping complex lipid associations and exploration of interactions that characterise biological ‘omics’ approaches. Looking back, it is evident that electrospray ionisation (ESI) has influenced and shaped lipidomics more than any other technique. When coupled to tandem MS (MS/MS), ESI-MS/MS led to the first lipidomic data sets obtained from cellular phospholipids, an approach that is now widely employed by almost all labs working on membrane lipids. The system is applicable to direct infusion or gunshot experiments used to analyse relatively crude lipid extracts without any prior separation or purification, an approach described as global lipidomics. Furthermore, ESI is easily coupled to liquid chromatography (LC) allowing for the development of LC-MS/MS-based targeted approaches. Spectrometers used for such applications include triple quadrupoles (Q3) that are particularly good for quantitative analysis through multiple reaction monitoring, although generally characterised by low mass resolution, and hybrid systems where quadrupoles are coupled to ion traps (Q-Trap) or time-of-flight (Q-TOF) analysers that allow for both quantitative approaches and high mass accuracy. Recently, we have seen an increase in the use of ultrahigh performance liquid chromatography (UPLC) coupled to MS in an attempt to increase the high-through-put efficiency of lipidomic analyses, whilst the availability of spectrometers with high mass accuracy and resolving power, such as the new linear ion trap-Orbitrap instruments, have started to make an impact on the field. Another emerging direction for lipidomics is marked by the appearance of publications on lipid imaging using matrix-assisted laser desorption ionisation (MALDI). MALDI-TOF permits identification of the spatial distribution and localisation of various lipid species in tissue slices, an area that is anticipated to generate exciting findings. Some of the main challenges faced by lipidomics stem out of the nature of its subject matter: lipids are not a uniform class of compounds; unlike genes or proteins, they are not composed of similar units and, because of their structural and chemical diversity, we have no means of predicting neither the type nor the number of lipid species present in any given biological system. Furthermore, there is no single extraction or analytical protocol applicable to all lipid classes, consequently we are restricted in our ability to reliably map the thousands of lipid species present in a particular sample, following one single uniform approach. Currently, this problem is addressed through the development of targeted approaches informed and directed by the properties of individual lipid classes, e.g. sphingolipid or eicosanoid lipidomics. Even in this case, there are issues around the accurate quantitation of new lipid species identified by lipidomics. This need for synthetic lipid standards calls for close collaboration with organic chemists. Global lipidomic approaches can generate an overwhelming number of data points that require computer assisted data analysis and management, an obvious area of interaction with bioinformatics. Recent publications indicate that this is an active area of research that is expected to expand as we move towards integrated approaches including lipidomics, transcriptomics and proteomics, brought together to address systems biology and systems medicine applications. Another important issue is the curation of lipidomic data: over time we have gathered and will continue to generate information on the lipidome of various cells, tissues and clinical samples. This data need to be collected in a coherent manner and made available for meta-analysis, comparative studies and further research. Although some consortia have started to make their data available through dedicated web sites, there is strong need for organised and sustained effort to capture this activity. So, what does the future hold for lipidomics? Where do we go from here? Are we going to see the formation of large research units dedicated to lipidomics in a way similar to what has happened to proteomics and genomics? Are we going to see lipidomic maps of cells and tissues used in systems medicine, biomarker discovery, drug development and personalised treatment? Although it is not easy to make predictions, it is evident that lipidomics is influencing the current thinking in many fields of research and is making a strong impact in biology and medicine. Lipidomics is already part of studies into cardiovascular disease, diabetes, brain disorders, multiple sclerosis, obesity, all characterised by altered lipid biochemistry. New technologies will undoubtedly increase our analytical capabilities, but, I strongly believe that it is the actual application of lipidomics that will generate breakthroughs and innovation in biosciences.